In particular, a key driver for vision loss in retinal diseases such as neovascular age-related macular degeneration is the accumulation of retinal edema or fluid. Out of the two components of retinal edema, intraretinal cystoid fluid (IRC) leads to severe vision loss. Conversely, recent evidence suggests that subretinal fluid (SRF) may be associated with better visual acuity. A precise classification, quantification and prediction of IRC and SRF may be of great importance for disease management. Similarly, a wide spectrum of other quantifiable morphologic objects may be present in the retina, which may be relevant for visual function, diagnosis, disease management and prediction of visual function.
A conventional method for processing optical coherence tomography data for automatic cyst detection is described in reference [1]. But, the method described in reference [1] has disadvantages in the calculating speed and in the necessary accuracy.
Accordingly, it is an aspect of the present invention to improve the processing of image data, like optical coherence tomography data.